Customer Analytics: How to Boost Loyalty & Reduce Subscriber Churn

Our phones are with us nearly 24/7. For many of us, it’s the first thing we look at in the morning and the last thing before bed. (In fact the attachment is so strong that phone separation has developed as a real fear called ”nomophobia.”) Our loyalty, however, doesn’t extend to our service providers. If we’re not happy with coverage, have too many dropped calls, or simply see a better deal, we can be quick to jump.

This creates a challenge for service providers who struggle to understand which customers are at-risk of switching (customer churn), and then taking action to prevent this from happening. People in marketing, operations and customer care responsible for running these efforts need to move fast so they can identify issues and effectively reduce customer churn.

Here at ThoughtSpot, we recently started working with one telecom provider who needed to get their customer analytics dialed in. This group wanted to give all their business users access to customer and phone usage data so they could run their own reports and identify at-risk customers for churn.

Previously decision makers at the company had to wait for BI analysts to run reports from the legacy BI tool—Cognos. In one example, marketing teams were waiting 90 days to get the results from their new campaigns. This meant they were missing valuable insights, and their campaigns resulted in cannibalization and lost revenue.

Their head of BI need a solution that would allow end users direct access to their data, without waiting for a team of experts to build them another report. But ease of use was just one piece of the puzzle. They also needed a solution that could handle terabytes of data from multiple systems, without impacting performance or requiring heavy maintenance and support.

In addition to identifying customers most likely to churn, business users are now asking questions in ThoughtSpot to identify insights like top-performing campaigns, areas of revenue leakage, and phone plans with the greatest number of complaints. In particular:

Marketers and Brand Managers are running campaign attribution analyses to identify the top performing campaigns across channels, brands and segments to improve targeting and maximize lead flow and campaign ROI.​

Sales and Distribution Managers are performing inventory and supply-chain analysis to understand sales trends across product lines and regions, and reduce inventory shortages and stockouts.

Customer Care and Operations are analyzing service cases across phone lines, carriers and regions to identify the root cause of service issues faster, increase customer satisfaction and reduce customer churn. They have also been able to quickly identify fraud patterns and decrease revenue loss as a result.